► A CSR is only required for 15 of the 19 reference BLHC chemicals (79%). Three BLHC chemi-cals (16%) have an intermediate registration and one BLHC chemical (5%) is registered at a tonnage band of 1-10 t/a. In both cases, a CSR is not required according to the REACH Regu-lation. For the 15 BLHC chemicals with a CSR, an exposure estimate was available in the CSR.
However, the situation is more complex for HPV and MPV chemicals;
► CSRs were not available for evaluation for 6 HPV and 6 MPV chemicals, because these only have an intermediate registration. In addition, a CSR is not required for 3 HPV chemicals due to the low tonnage;
► An exposure estimate (for workers) is available for the majority of substances that require a CSR. However, such an exposure estimate is not included in the CSR for 9 HPV and 7 MPV chemicals, almost exclusively due the fact that these substances are not classified. As a con-sequence, an exposure estimate is not required under the REACH Regulation.
► In the 5YU, the Reach Registration Deadline included BLHC and HPV chemicals. In the 10YU, BLHC, HPV and MPV substances are evaluated.
► Figure below shows the aggregated Risk Score the impact area of workers. For the 94 reference substances under evaluation in the 10YU (BLHC, HPV and MPV chemicals combined), the Risk Score for the baseline was 295. 10 years on, the Risk Score for the 94 reference substances has reduced to 5.1, which is 18% of the baseline score. For
comparison, this decline is similar that observed in the 5YU, when a decrease of the
aggregated Risk Score from 42 to 8.7 (21%) was observed for the 62 reference substances.
5 This value is higher than the aggregated baseline Risk Score of 16 for all 237 reference substances. This finding is not surprising since the fraction of BLHC chemicals (19/94, 20%) is higher than in the entire set (25/237, 11%) and Risk Scores are particularly high for BLHC chemicals.
Figure 6: Aggregated risk (geometric mean, GM), for Workers
Source: Bunke D et al (2017): REACH baseline study – 10 years update
► The following Figure shows the aggregated Quality Scores. For the 94 reference substances under evaluation in the 10YU, the total baseline Quality Score was 28. This value reflects a better quality than the aggregated Quality Score of 42 for all 237 reference substances6.
► In the 10YU, the aggregated Quality Score for the 94 reference substances declines to 12 (43% of the baseline value). This decline is somewhat stronger to the one observed in the 5YU, when a decrease of the aggregated Quality Score from 21 to 11 (52%) was observed for the 62 reference substances.
Figure 7: Aggregated quality score (geometric mean, GM), for Workers
Source: Bunke D et al (2017): REACH baseline study – 10 years update
6 As before, this is not surprising since the fraction of BLHC and HPV chemicals in the 10YU sample (71/94, 76%) is higher than in the entire set (90/237, 38%) and BLHC and HPV chemicals can be expected to have more data than MPV and LPV chemicals. A simi-lar pattern was also observed in the 5YU.
► In conclusion, there is a clear decline in the Aggregated Risk Score and an evident increase in the quality for the 94 reference substances evaluated in the 10YU, which reflects the fact that new data became available (DNEL not available at baseline). The trend of declining Risk Scores and Quality Scores is similar to the one reported in the 5YU, but it seems to be slightly more pronounced in the 10YU.
► No major changes occurred for BLHC and HPV chemicals from the 5YU to the 10YU. The most prominent changes are observed for MPV chemicals, thus highlighting a better quality of the data.
► Overall, the evaluations for the impact area workers show that the implementation of the REACH Regulation leads to lower Risk Scores and improved quality of the underlying data in the 10YU when compared with the pre-REACH baseline. Lower Risk Scores and better data quality are observed in the aggregated as well as the group-specific (BLHC, HPV and MPV chemicals) evaluations. For the impact area workers, the results of the 10 YU confirm the ones obtained in the 5YU for a larger set of chemicals. Compared to the decline in Risk and Quality Scores from baseline to the 10YU, the changes between the 5YU and the 10YU are small.
► The 10YU in the impact area environment confirms the trend observed for the 5YU (de-creases in Risk Scores and RCRs as well as an improved quality) for a larger dataset of BLHC and HPV chemicals. MPV chemicals showed a very similar decrease in Risk Scores, RCRs and Quality Scores (improved quality) from baseline to the 10YU as the ones observed for HPV chemicals in the 5YU. It is also observed that the decrease in Risk Scores and Quality Scores is more evident in the 10YU compared to the 5YU for the BLHC chemicals.
► Overall, the evaluations show that the implementation of the REACH Regulation leads to lower Risk Scores for the environment and improved quality of the underlying data in the 10YU when compared with the pre-REACH baseline. It is observed that the toxicity estimate is of overall importance and that REACH appears to lead to an "improved toxicity", i.e. the eco-toxicity dataset for many substances has been improved leading to higher toxicity esti-mates corresponding to that the assessed toxicity has been decreased.
► Registration dossiers brought useful information on:
⚫ uses: only 39% of evaluated substances are intended to be used by consumers in prod-ucts or articles;
⚫ toxicity: DNELs for general population were provided in CSRs for 60% of the evaluated substances;
⚫ exposure: exposure estimates were provided for 62% of the used substances.
► The variations of the aggregated Risk and Quality Scores from baseline to the 10YU show a lower estimated risk (RS decline from 7.0 to 1.0) and a better quality of the data (QS decline from 50 to 17), with the same tendency for HPV and MPV chemicals.
► Between baseline and the 10YU, the toxicity estimates increased more than the exposure es-timates, leading to a decrease of the Risk Characterization Ratio and the Risk Score. As a re-sult, the number of substances with RCRs above 1 decreased from 23 at baseline to 11 in the 10YU among 32 “used” substances.
Man via the environment
► Among the 94 substances registered at the time of this evaluation, specific data on exposure for humans via environment is reported for 39 of them and 4 substances presented meas-ured data. The data for the other substances are calculated by modelling.
► Decline in the Risk Scores and improvements in the quality of data.
► Correlation with substance evaluation: according to the data, inclusion of a substance in sub-stance evaluation makes it more likely that the toxicity or exposure estimate has changed be-tween the 5YU and the 10YU.
► Correlation with dossier evaluation: Substances with changes in toxicity or exposure esti-mates are more likely to have been covered by dossier evaluation. For example, 4 of the 5 BLHC chemicals that are included in the dossier evaluation process experienced altered tox-icity or exposure estimates between the 5YU and the 10YU (80%). In contrast, only 4 of the 14 BLHC chemicals (29%) that are not in the dossier evaluation process experienced such changes. Again, the findings are similar for HPV chemicals.
► Correlation with soft measures: Evidence suggests that such measures initiated by ECHA did not generate significant results between the 5YU and the 10YU. The CSR was updated before the soft measure was mandated.
Main gaps identified:
► Tonnage information is extracted from ECHA – gaps depend on the limitations of the dossi-ers: E.g.: manufacture/import of given substance at different tonnages every year.
► Dossiers tend to report upper end figure for tonnages, which leads to overestimation